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JMP Descriptive and Predictive Analytics Assignment (II)
Assignment Overview
Objective
To provide you with some hands-on experience with the JMP and how it is used to support decision-making in organizations.
This assignment assumes that you only have basic familiarity with JMP focusing on the descriptive and predictive analyses from the hands-on tutorial that was provided to you in class.
Grade
This assignment is worth 10% of your total course grade. There are 8 parts in this assignment and each part contains a set of questions. See the marking scheme:
Due date
Tuesday, October 17 at 11:59 PM (23:59). Your completed assignment should be uploaded through Avenue to Learn to the folder "JMP: Descriptive & Predic- tive Analytics Assignment (2)" under Assessments -- > Assignments.
The overdue penalty is 20% of the total assignment mark per day.
Submitting the Assignment
Part 1 Part 2 Part 3 Part 4 Part 5 Part 6 Part 7 Part 8 Total
10 marks 10 marks 10 marks 12 marks 10 marks 20 marks 15 marks 13 marks 100 marks
Submit only one MS Word or PDF file. If you submit more than one file, the most recent will be graded.
Please name the file as "Class section-Student number-First name-Last name" (for example if you are in section 1 and your name is John Smith and your student number is 1234567, name the files C01-1234567- John-Smith).
The Word File
Create an MS Word file that includes the answers to the questions and any screenshots, graphs, and tables as instructed in the assignment questions. You will need to submit the finalized version of this file (as either Word or PDF ) to receive the grades for the assignment.
In case you have any questions regarding the assignment, please contact Kimia Ansari ([email protected])
How to Logon to JMP Pro 15
For Windows users:
- Download Windows JMP 15:
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2. For Mac users:
- Download OSX JMP 15:
Virtual Lab users:
Sign in to
For the instruction of JMP installation and activation, you can search online. There are lots of resources. For instance, check the following links for Windows and Mac users:
The instructions for Virtual lab can be found here:
To answer the questions in this assignment, you need to use the Consumer Preferences.jmp data table, which contains data about consumers' preferences in using floss and brush. To access the data, follow the path below:
JMP→help→Sample data library→Consumer Preferences.jmp
BACKGROUND: You are hired by a company to understand consumers and their preferences better. The
company expects you to use the JMP skill you noted on your resume to help with these analyses. Part 1. Answer the following questions using a Histogram (Analyze→Distribution):
1.1. What is the average salary of consumers?
消费者的平均工资是多少?
在图中添加“离群值箱线图”并回答以下问题:
Add the "outlier box plot" to the figure and answer the following questions:
1.2 Are there any consumers whose salary is either extremely high or extremely low compared to the
other consumers? Why? If there are any outliers, exclude them from the data table and "Redo"
the analysis for further questions.
1.3 What is the largest value, median, and smallest value in the new Histogram? What does each
value mean?
1.4 Find the new interquartile range and explain whether the box plot is skewed right or left.
* Copy both figures you got in JMP here.
是否有消费者的工资与其他消费者相比极高或极低?为什么?如果存在任何异常值，请 将其从数据表中排除，并“重做”分析以解决进一步的问题。
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Part 2. Answer the following questions using a Bar chart (Graph→Graph Builder):
2.1. What is the most common gender of the consumers? How many consumers are female, and how many are male?
2.2. What is the most common marital status of the consumers? How many consumers are single, and how many are not single?
2.3. What are the main differences between the histogram and bar chart? (Write 3 differences in bullet points)
* Copy the bar charts you got in JMP here.
Part 3. Answer the following questions using a Scatterplot (Graph→Scatterplot Matrix): 3.1. What is the relationship between floss cost and consumers' age (age in years)? Why?
(Add "Floss cost" to the Y-axis and "Age in years" to the X-axis.)
3.2. What is the relationship between salary and consumers' age (age in years)? Why? (Add "Salary" to the Y-axis and "Age in years" to the X-axis.)
Note: To show the relationship, you need to add the fit line to the diagram.
* Copy Scatterplots you got in JMP here.
* Draw a Scatterplot 3D (Graph → Scatterplot 3D) of the above relationships (including all three variables) and copy it here.
Part 4. Follow the instruction and then answer the questions using a Bubble Plot (Graph→Bubble Plot):
• Use the bubble plot by considering the salary of consumers in the Y-axis and consumers' age (age in years) in the X-axis. Size the bubbles based on the "years in current position", and color the bubbles based on the "gender".
4.1. Which consumer receives the highest salary? (Write the row number) How much is this consumer's salary? Is this consumer a female or male? How old is this consumer? What is the number of years this consumer has been at the current employer?
4.2. What are the main differences between the Scatterplot and the Bubble plot? (Write your answer in 2 bullet points)
* Copy the bubble plot you got in JMP.
Part 5. Answer the following question using Graph Builder (Graph→Graph Builder):
• Is there any difference between males and females in the amount of money they spend on purchasing toothpaste? Show this relation by using two different graphs in the Graph builder and then interpret the results based on the outcome of each graph.
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Part 6. Follow the instruction and answer the following question using Clustering (Analyze→ Clustering):
• Use "age in years", "years in current position", and "years at current employer" variables in your dataset and use the K-means Clustering method to divide your data into different clusters. Consider the number of clusters to be 3.
• What is the number of data points in each cluster? What is the mean value for "consumers' age" (age in years), "years at current employer", and "years in current position" in each cluster?
• Show the clusters in both Biplot and Biplot 3D types.
▪ Note: Click on the top red triangle and select Biplot and Biplot 3D type.
• Take screenshots of the results you get from JMP.
• Write about the main insights you obtained after clustering the data? (Write at least 2 insights you
obtain in bullet points)
Part 7. Complete this part using Partitioning (Analyze→Predictive Modeling→Partition): This part needs to analyze the consumers' tooth brushing behavior (i.e., "Brush") by creating a decision
tree. Make the analysis by classifying the consumers based on their "gender" and "age in years". Note: Set the validation portion to 0.3 and the number of splits to 3.
• Add a screenshot of the graph (partition for Brush) and the decision tree.
• Briefly compare the resulting age-gender groups' (e.g., males under 58 years old) tooth brushing
behavior based on the decision tree.
Note: Click on the top red triangle and select Display Options > Show Split Prob to show Rates (proportion of observations) and Probs (predicted probabilities) for the response levels in each leaf.
Part 8. Complete this part and answer the following questions using Regression (Analyze→Fit Y by X):
Do a regression analysis as below:
Use "Salary" as the response variable and "Age in years" as the factor variable. To fit the regression line, click on the red triangle and select Fit Line.
• Take the screenshot of the results you get from JMP.
• Find 1) the amount on average a member of this population earns, and 2) how much on average a
60 years old consumer earns more in comparison to a 25 years old consumer.
• Do we have a good fit between the model and data? Why?
Good luck ���
